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首页> 外文会议>International Conference on Computational Science(ICCS 2006) pt.1; 20060528-31; Reading(GB) >Parallel Optimization Methods Based on Direct Search
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Parallel Optimization Methods Based on Direct Search

机译：基于直接搜索的并行优化方法

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摘要

This paper is focused in the parallelization of Direct Search Optimization methods, which are part of the family of derivative-free methods. These methods are known to be quite slow, but are easily par-allelizable, and have the advantage of achieving global convergence in some problems where standard Newton-like methods (based on derivatives) fail. These methods have been tested with the Inverse Additive Singular Value Problem, which is a difficult highly nonlinear problem. The results obtained have been compared with those obtained with derivative methods; the efficiency of the parallel versions has been studied.
机译：本文着重于直接搜索优化方法的并行化，这是无导数方法系列的一部分。众所周知，这些方法速度很慢，但是很容易实现等位化，并且具有在某些类似标准牛顿法（基于导数）失败的问题中实现全局收敛的优势。这些方法已通过反加法奇异值问题进行了测试，这是一个困难的高度非线性问题。将获得的结果与通过导数法获得的结果进行了比较；已经研究了并行版本的效率。

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